State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, China.
Institute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
BMJ Open. 2021 Sep 7;11(9):e047227. doi: 10.1136/bmjopen-2020-047227.
To evaluate epidemiological characteristics and transmission dynamics of COVID-19 outbreak resurged in Beijing and to assess the effects of three non-pharmaceutical interventions.
Descriptive and modelling study based on surveillance data of COVID-19 in Beijing.
Outbreak in Beijing.
The database included 335 confirmed cases of COVID-19.
To conduct spatiotemporal analyses of the outbreak, we collected individual records on laboratory-confirmed cases of COVID-19 from 11 June 2020 to 5 July 2020 in Beijing, and visitor flow and products transportation data of Xinfadi Wholesale Market. We also built a modified susceptible-exposed-infected-removed model to investigate the effect of interventions deployed in Beijing.
We found that the staff working in the market (52.2%) and the people around 10 km to this epicentre (72.5%) were most affected, and the population mobility entering-exiting Xinfadi Wholesale Market significantly contributed to the spread of COVID-19 (p=0.021), but goods flow of the market had little impact on the virus spread (p=0.184). The prompt identification of Xinfadi Wholesale Market as the infection source could have avoided a total of 25 708 (95% CI 13 657 to 40 625) cases if unnoticed transmission lasted for a month. Based on the model, we found that active screening on targeted population by nucleic acid testing alone had the most significant effect.
The non-pharmaceutical interventions deployed in Beijing, including localised lockdown, close-contact tracing and community-based testing, were proved to be effective enough to contain the outbreak. Beijing has achieved an optimal balance between epidemic containment and economic protection.
评估北京新冠肺炎疫情反弹的流行病学特征和传播动态，并评估三种非药物干预措施的效果。
基于北京新冠肺炎监测数据的描述性和建模研究。
北京疫情爆发地。
数据库包含 335 例新冠肺炎确诊病例。
为了对疫情进行时空分析，我们收集了 2020 年 6 月 11 日至 7 月 5 日期间北京实验室确诊的新冠肺炎病例的个体记录，以及新发地批发市场的游客流量和产品运输数据。我们还建立了一个改良的易感-暴露-感染-消除模型，以调查在北京部署的干预措施的效果。
我们发现，市场工作人员（52.2%）和该中心周围 10 公里范围内的人员（72.5%）受影响最大，进入-离开新发地批发市场的人口流动对新冠肺炎的传播有显著贡献（p=0.021），但市场货物流动对病毒传播影响不大（p=0.184）。如果新发地批发市场作为感染源未被及时发现，持续传播一个月可能会导致 25708 例（95%CI 13657 至 40625 例）病例。基于模型，我们发现，仅对目标人群进行核酸检测的主动筛查效果最显著。
北京部署的非药物干预措施，包括局部封锁、密切接触者追踪和社区检测，已被证明足以遏制疫情。北京在控制疫情和保护经济之间取得了最佳平衡。
